activity
20192022
most citedExploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition

75 citations · 135 across the 15 of their papers we have counts for

collaborators

20 papers

cs.CV20225 cited

IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic Segmentation

Lihua Fu, Haoyue Tian, Xiangping Bryce Zhai +2

Semantic segmentation usually benefits from global contexts, fine localisation information, multi-scale features, etc. To advance Transformer-based segmenters with these aspects, w…

cs.CV20222 cited

AU-Aware Vision Transformers for Biased Facial Expression Recognition

Shuyi Mao, Xinpeng Li, Qingyang Wu +1

Studies have proven that domain bias and label bias exist in different Facial Expression Recognition (FER) datasets, making it hard to improve the performance of a specific dataset…

cs.CV20221 cited

Video Frame Interpolation Based on Deformable Kernel Region

Haoyue Tian, Pan Gao, Xiaojiang Peng

Video frame interpolation task has recently become more and more prevalent in the computer vision field. At present, a number of researches based on deep learning have achieved gre…

cs.CV2022

Stereo Matching with Cost Volume based Sparse Disparity Propagation

Wei Xue, Xiaojiang Peng

Stereo matching is crucial for binocular stereo vision. Existing methods mainly focus on simple disparity map fusion to improve stereo matching, which require multiple dense or spa…

cs.CV20215 cited

Spatial and Temporal Networks for Facial Expression Recognition in the Wild Videos

Shuyi Mao, Xinqi Fan, Xiaojiang Peng

The paper describes our proposed methodology for the seven basic expression classification track of Affective Behavior Analysis in-the-wild (ABAW) Competition 2021. In this task, f…

cs.CV20217 cited

Detecting Human-Object Interaction via Fabricated Compositional Learning

Zhi Hou, Baosheng Yu, Yu Qiao +2

Human-Object Interaction (HOI) detection, inferring the relationships between human and objects from images/videos, is a fundamental task for high-level scene understanding. Howeve…